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Diffstat (limited to 'klm/lm/builder')
25 files changed, 2252 insertions, 0 deletions
diff --git a/klm/lm/builder/Makefile.am b/klm/lm/builder/Makefile.am new file mode 100644 index 00000000..b5c147fd --- /dev/null +++ b/klm/lm/builder/Makefile.am @@ -0,0 +1,28 @@ +bin_PROGRAMS = builder + +builder_SOURCES = \ + main.cc \ + adjust_counts.cc \ + adjust_counts.hh \ + corpus_count.cc \ + corpus_count.hh \ + discount.hh \ + header_info.hh \ + initial_probabilities.cc \ + initial_probabilities.hh \ + interpolate.cc \ + interpolate.hh \ + joint_order.hh \ + multi_stream.hh \ + ngram.hh \ + ngram_stream.hh \ + pipeline.cc \ + pipeline.hh \ + print.cc \ + print.hh \ + sort.hh + +builder_LDADD = ../libklm.a ../../util/double-conversion/libklm_util_double.a ../../util/stream/libklm_util_stream.a ../../util/libklm_util.a $(BOOST_THREAD_LIBS) + +AM_CPPFLAGS = -W -Wall -I$(top_srcdir)/klm + diff --git a/klm/lm/builder/README.md b/klm/lm/builder/README.md new file mode 100644 index 00000000..be0d35e2 --- /dev/null +++ b/klm/lm/builder/README.md @@ -0,0 +1,47 @@ +Dependencies +============ + +Boost >= 1.42.0 is required. + +For Ubuntu, +```bash +sudo apt-get install libboost1.48-all-dev +``` + +Alternatively, you can download, compile, and install it yourself: + +```bash +wget http://sourceforge.net/projects/boost/files/boost/1.52.0/boost_1_52_0.tar.gz/download -O boost_1_52_0.tar.gz +tar -xvzf boost_1_52_0.tar.gz +cd boost_1_52_0 +./bootstrap.sh +./b2 +sudo ./b2 install +``` + +Local install options (in a user-space prefix directory) are also possible. See http://www.boost.org/doc/libs/1_52_0/doc/html/bbv2/installation.html. + + +Building +======== + +```bash +bjam +``` +Your distribution might package bjam and boost-build separately from Boost. Both are required. + +Usage +===== + +Run +```bash +$ bin/lmplz +``` +to see command line arguments + +Running +======= + +```bash +bin/lmplz -o 5 <text >text.arpa +``` diff --git a/klm/lm/builder/TODO b/klm/lm/builder/TODO new file mode 100644 index 00000000..cb5aef3a --- /dev/null +++ b/klm/lm/builder/TODO @@ -0,0 +1,5 @@ +More tests! +Sharding. +Some way to manage all the crazy config options. +Option to build the binary file directly. +Interpolation of different orders. diff --git a/klm/lm/builder/adjust_counts.cc b/klm/lm/builder/adjust_counts.cc new file mode 100644 index 00000000..a6f48011 --- /dev/null +++ b/klm/lm/builder/adjust_counts.cc @@ -0,0 +1,216 @@ +#include "lm/builder/adjust_counts.hh" +#include "lm/builder/multi_stream.hh" +#include "util/stream/timer.hh" + +#include <algorithm> + +namespace lm { namespace builder { + +BadDiscountException::BadDiscountException() throw() {} +BadDiscountException::~BadDiscountException() throw() {} + +namespace { +// Return last word in full that is different. +const WordIndex* FindDifference(const NGram &full, const NGram &lower_last) { + const WordIndex *cur_word = full.end() - 1; + const WordIndex *pre_word = lower_last.end() - 1; + // Find last difference. + for (; pre_word >= lower_last.begin() && *pre_word == *cur_word; --cur_word, --pre_word) {} + return cur_word; +} + +class StatCollector { + public: + StatCollector(std::size_t order, std::vector<uint64_t> &counts, std::vector<Discount> &discounts) + : orders_(order), full_(orders_.back()), counts_(counts), discounts_(discounts) { + memset(&orders_[0], 0, sizeof(OrderStat) * order); + } + + ~StatCollector() {} + + void CalculateDiscounts() { + counts_.resize(orders_.size()); + discounts_.resize(orders_.size()); + for (std::size_t i = 0; i < orders_.size(); ++i) { + const OrderStat &s = orders_[i]; + counts_[i] = s.count; + + for (unsigned j = 1; j < 4; ++j) { + // TODO: Specialize error message for j == 3, meaning 3+ + UTIL_THROW_IF(s.n[j] == 0, BadDiscountException, "Could not calculate Kneser-Ney discounts for " + << (i+1) << "-grams with adjusted count " << (j+1) << " because we didn't observe any " + << (i+1) << "-grams with adjusted count " << j << "; Is this small or artificial data?"); + } + + // See equation (26) in Chen and Goodman. + discounts_[i].amount[0] = 0.0; + float y = static_cast<float>(s.n[1]) / static_cast<float>(s.n[1] + 2.0 * s.n[2]); + for (unsigned j = 1; j < 4; ++j) { + discounts_[i].amount[j] = static_cast<float>(j) - static_cast<float>(j + 1) * y * static_cast<float>(s.n[j+1]) / static_cast<float>(s.n[j]); + UTIL_THROW_IF(discounts_[i].amount[j] < 0.0 || discounts_[i].amount[j] > j, BadDiscountException, "ERROR: " << (i+1) << "-gram discount out of range for adjusted count " << j << ": " << discounts_[i].amount[j]); + } + } + } + + void Add(std::size_t order_minus_1, uint64_t count) { + OrderStat &stat = orders_[order_minus_1]; + ++stat.count; + if (count < 5) ++stat.n[count]; + } + + void AddFull(uint64_t count) { + ++full_.count; + if (count < 5) ++full_.n[count]; + } + + private: + struct OrderStat { + // n_1 in equation 26 of Chen and Goodman etc + uint64_t n[5]; + uint64_t count; + }; + + std::vector<OrderStat> orders_; + OrderStat &full_; + + std::vector<uint64_t> &counts_; + std::vector<Discount> &discounts_; +}; + +// Reads all entries in order like NGramStream does. +// But deletes any entries that have <s> in the 1st (not 0th) position on the +// way out by putting other entries in their place. This disrupts the sort +// order but we don't care because the data is going to be sorted again. +class CollapseStream { + public: + CollapseStream(const util::stream::ChainPosition &position) : + current_(NULL, NGram::OrderFromSize(position.GetChain().EntrySize())), + block_(position) { + StartBlock(); + } + + const NGram &operator*() const { return current_; } + const NGram *operator->() const { return ¤t_; } + + operator bool() const { return block_; } + + CollapseStream &operator++() { + assert(block_); + if (current_.begin()[1] == kBOS && current_.Base() < copy_from_) { + memcpy(current_.Base(), copy_from_, current_.TotalSize()); + UpdateCopyFrom(); + } + current_.NextInMemory(); + uint8_t *block_base = static_cast<uint8_t*>(block_->Get()); + if (current_.Base() == block_base + block_->ValidSize()) { + block_->SetValidSize(copy_from_ + current_.TotalSize() - block_base); + ++block_; + StartBlock(); + } + return *this; + } + + private: + void StartBlock() { + for (; ; ++block_) { + if (!block_) return; + if (block_->ValidSize()) break; + } + current_.ReBase(block_->Get()); + copy_from_ = static_cast<uint8_t*>(block_->Get()) + block_->ValidSize(); + UpdateCopyFrom(); + } + + // Find last without bos. + void UpdateCopyFrom() { + for (copy_from_ -= current_.TotalSize(); copy_from_ >= current_.Base(); copy_from_ -= current_.TotalSize()) { + if (NGram(copy_from_, current_.Order()).begin()[1] != kBOS) break; + } + } + + NGram current_; + + // Goes backwards in the block + uint8_t *copy_from_; + + util::stream::Link block_; +}; + +} // namespace + +void AdjustCounts::Run(const ChainPositions &positions) { + UTIL_TIMER("(%w s) Adjusted counts\n"); + + const std::size_t order = positions.size(); + StatCollector stats(order, counts_, discounts_); + if (order == 1) { + // Only unigrams. Just collect stats. + for (NGramStream full(positions[0]); full; ++full) + stats.AddFull(full->Count()); + stats.CalculateDiscounts(); + return; + } + + NGramStreams streams; + streams.Init(positions, positions.size() - 1); + CollapseStream full(positions[positions.size() - 1]); + + // Initialization: <unk> has count 0 and so does <s>. + NGramStream *lower_valid = streams.begin(); + streams[0]->Count() = 0; + *streams[0]->begin() = kUNK; + stats.Add(0, 0); + (++streams[0])->Count() = 0; + *streams[0]->begin() = kBOS; + // not in stats because it will get put in later. + + // iterate over full (the stream of the highest order ngrams) + for (; full; ++full) { + const WordIndex *different = FindDifference(*full, **lower_valid); + std::size_t same = full->end() - 1 - different; + // Increment the adjusted count. + if (same) ++streams[same - 1]->Count(); + + // Output all the valid ones that changed. + for (; lower_valid >= &streams[same]; --lower_valid) { + stats.Add(lower_valid - streams.begin(), (*lower_valid)->Count()); + ++*lower_valid; + } + + // This is here because bos is also const WordIndex *, so copy gets + // consistent argument types. + const WordIndex *full_end = full->end(); + // Initialize and mark as valid up to bos. + const WordIndex *bos; + for (bos = different; (bos > full->begin()) && (*bos != kBOS); --bos) { + ++lower_valid; + std::copy(bos, full_end, (*lower_valid)->begin()); + (*lower_valid)->Count() = 1; + } + // Now bos indicates where <s> is or is the 0th word of full. + if (bos != full->begin()) { + // There is an <s> beyond the 0th word. + NGramStream &to = *++lower_valid; + std::copy(bos, full_end, to->begin()); + to->Count() = full->Count(); + } else { + stats.AddFull(full->Count()); + } + assert(lower_valid >= &streams[0]); + } + + // Output everything valid. + for (NGramStream *s = streams.begin(); s <= lower_valid; ++s) { + stats.Add(s - streams.begin(), (*s)->Count()); + ++*s; + } + // Poison everyone! Except the N-grams which were already poisoned by the input. + for (NGramStream *s = streams.begin(); s != streams.end(); ++s) + s->Poison(); + + stats.CalculateDiscounts(); + + // NOTE: See special early-return case for unigrams near the top of this function +} + +}} // namespaces diff --git a/klm/lm/builder/adjust_counts.hh b/klm/lm/builder/adjust_counts.hh new file mode 100644 index 00000000..f38ff79d --- /dev/null +++ b/klm/lm/builder/adjust_counts.hh @@ -0,0 +1,44 @@ +#ifndef LM_BUILDER_ADJUST_COUNTS__ +#define LM_BUILDER_ADJUST_COUNTS__ + +#include "lm/builder/discount.hh" +#include "util/exception.hh" + +#include <vector> + +#include <stdint.h> + +namespace lm { +namespace builder { + +class ChainPositions; + +class BadDiscountException : public util::Exception { + public: + BadDiscountException() throw(); + ~BadDiscountException() throw(); +}; + +/* Compute adjusted counts. + * Input: unique suffix sorted N-grams (and just the N-grams) with raw counts. + * Output: [1,N]-grams with adjusted counts. + * [1,N)-grams are in suffix order + * N-grams are in undefined order (they're going to be sorted anyway). + */ +class AdjustCounts { + public: + AdjustCounts(std::vector<uint64_t> &counts, std::vector<Discount> &discounts) + : counts_(counts), discounts_(discounts) {} + + void Run(const ChainPositions &positions); + + private: + std::vector<uint64_t> &counts_; + std::vector<Discount> &discounts_; +}; + +} // namespace builder +} // namespace lm + +#endif // LM_BUILDER_ADJUST_COUNTS__ + diff --git a/klm/lm/builder/adjust_counts_test.cc b/klm/lm/builder/adjust_counts_test.cc new file mode 100644 index 00000000..68b5f33e --- /dev/null +++ b/klm/lm/builder/adjust_counts_test.cc @@ -0,0 +1,106 @@ +#include "lm/builder/adjust_counts.hh" + +#include "lm/builder/multi_stream.hh" +#include "util/scoped.hh" + +#include <boost/thread/thread.hpp> +#define BOOST_TEST_MODULE AdjustCounts +#include <boost/test/unit_test.hpp> + +namespace lm { namespace builder { namespace { + +class KeepCopy { + public: + KeepCopy() : size_(0) {} + + void Run(const util::stream::ChainPosition &position) { + for (util::stream::Link link(position); link; ++link) { + mem_.call_realloc(size_ + link->ValidSize()); + memcpy(static_cast<uint8_t*>(mem_.get()) + size_, link->Get(), link->ValidSize()); + size_ += link->ValidSize(); + } + } + + uint8_t *Get() { return static_cast<uint8_t*>(mem_.get()); } + std::size_t Size() const { return size_; } + + private: + util::scoped_malloc mem_; + std::size_t size_; +}; + +struct Gram4 { + WordIndex ids[4]; + uint64_t count; +}; + +class WriteInput { + public: + void Run(const util::stream::ChainPosition &position) { + NGramStream input(position); + Gram4 grams[] = { + {{0,0,0,0},10}, + {{0,0,3,0},3}, + // bos + {{1,1,1,2},5}, + {{0,0,3,2},5}, + }; + for (size_t i = 0; i < sizeof(grams) / sizeof(Gram4); ++i, ++input) { + memcpy(input->begin(), grams[i].ids, sizeof(WordIndex) * 4); + input->Count() = grams[i].count; + } + input.Poison(); + } +}; + +BOOST_AUTO_TEST_CASE(Simple) { + KeepCopy outputs[4]; + std::vector<uint64_t> counts; + std::vector<Discount> discount; + { + util::stream::ChainConfig config; + config.total_memory = 100; + config.block_count = 1; + Chains chains(4); + for (unsigned i = 0; i < 4; ++i) { + config.entry_size = NGram::TotalSize(i + 1); + chains.push_back(config); + } + + chains[3] >> WriteInput(); + ChainPositions for_adjust(chains); + for (unsigned i = 0; i < 4; ++i) { + chains[i] >> boost::ref(outputs[i]); + } + chains >> util::stream::kRecycle; + BOOST_CHECK_THROW(AdjustCounts(counts, discount).Run(for_adjust), BadDiscountException); + } + BOOST_REQUIRE_EQUAL(4UL, counts.size()); + BOOST_CHECK_EQUAL(4UL, counts[0]); + // These are no longer set because the discounts are bad. +/* BOOST_CHECK_EQUAL(4UL, counts[1]); + BOOST_CHECK_EQUAL(3UL, counts[2]); + BOOST_CHECK_EQUAL(3UL, counts[3]);*/ + BOOST_REQUIRE_EQUAL(NGram::TotalSize(1) * 4, outputs[0].Size()); + NGram uni(outputs[0].Get(), 1); + BOOST_CHECK_EQUAL(kUNK, *uni.begin()); + BOOST_CHECK_EQUAL(0ULL, uni.Count()); + uni.NextInMemory(); + BOOST_CHECK_EQUAL(kBOS, *uni.begin()); + BOOST_CHECK_EQUAL(0ULL, uni.Count()); + uni.NextInMemory(); + BOOST_CHECK_EQUAL(0UL, *uni.begin()); + BOOST_CHECK_EQUAL(2ULL, uni.Count()); + uni.NextInMemory(); + BOOST_CHECK_EQUAL(2ULL, uni.Count()); + BOOST_CHECK_EQUAL(2UL, *uni.begin()); + + BOOST_REQUIRE_EQUAL(NGram::TotalSize(2) * 4, outputs[1].Size()); + NGram bi(outputs[1].Get(), 2); + BOOST_CHECK_EQUAL(0UL, *bi.begin()); + BOOST_CHECK_EQUAL(0UL, *(bi.begin() + 1)); + BOOST_CHECK_EQUAL(1ULL, bi.Count()); + bi.NextInMemory(); +} + +}}} // namespaces diff --git a/klm/lm/builder/corpus_count.cc b/klm/lm/builder/corpus_count.cc new file mode 100644 index 00000000..abea4ed0 --- /dev/null +++ b/klm/lm/builder/corpus_count.cc @@ -0,0 +1,224 @@ +#include "lm/builder/corpus_count.hh" + +#include "lm/builder/ngram.hh" +#include "lm/lm_exception.hh" +#include "lm/word_index.hh" +#include "util/file.hh" +#include "util/file_piece.hh" +#include "util/murmur_hash.hh" +#include "util/probing_hash_table.hh" +#include "util/scoped.hh" +#include "util/stream/chain.hh" +#include "util/stream/timer.hh" +#include "util/tokenize_piece.hh" + +#include <boost/unordered_set.hpp> +#include <boost/unordered_map.hpp> + +#include <functional> + +#include <stdint.h> + +namespace lm { +namespace builder { +namespace { + +class VocabHandout { + public: + explicit VocabHandout(int fd) { + util::scoped_fd duped(util::DupOrThrow(fd)); + word_list_.reset(util::FDOpenOrThrow(duped)); + + Lookup("<unk>"); // Force 0 + Lookup("<s>"); // Force 1 + Lookup("</s>"); // Force 2 + } + + WordIndex Lookup(const StringPiece &word) { + uint64_t hashed = util::MurmurHashNative(word.data(), word.size()); + std::pair<Seen::iterator, bool> ret(seen_.insert(std::pair<uint64_t, lm::WordIndex>(hashed, seen_.size()))); + if (ret.second) { + char null_delimit = 0; + util::WriteOrThrow(word_list_.get(), word.data(), word.size()); + util::WriteOrThrow(word_list_.get(), &null_delimit, 1); + UTIL_THROW_IF(seen_.size() >= std::numeric_limits<lm::WordIndex>::max(), VocabLoadException, "Too many vocabulary words. Change WordIndex to uint64_t in lm/word_index.hh."); + } + return ret.first->second; + } + + WordIndex Size() const { + return seen_.size(); + } + + private: + typedef boost::unordered_map<uint64_t, lm::WordIndex> Seen; + + Seen seen_; + + util::scoped_FILE word_list_; +}; + +class DedupeHash : public std::unary_function<const WordIndex *, bool> { + public: + explicit DedupeHash(std::size_t order) : size_(order * sizeof(WordIndex)) {} + + std::size_t operator()(const WordIndex *start) const { + return util::MurmurHashNative(start, size_); + } + + private: + const std::size_t size_; +}; + +class DedupeEquals : public std::binary_function<const WordIndex *, const WordIndex *, bool> { + public: + explicit DedupeEquals(std::size_t order) : size_(order * sizeof(WordIndex)) {} + + bool operator()(const WordIndex *first, const WordIndex *second) const { + return !memcmp(first, second, size_); + } + + private: + const std::size_t size_; +}; + +struct DedupeEntry { + typedef WordIndex *Key; + Key GetKey() const { return key; } + Key key; + static DedupeEntry Construct(WordIndex *at) { + DedupeEntry ret; + ret.key = at; + return ret; + } +}; + +typedef util::ProbingHashTable<DedupeEntry, DedupeHash, DedupeEquals> Dedupe; + +const float kProbingMultiplier = 1.5; + +class Writer { + public: + Writer(std::size_t order, const util::stream::ChainPosition &position, void *dedupe_mem, std::size_t dedupe_mem_size) + : block_(position), gram_(block_->Get(), order), + dedupe_invalid_(order, std::numeric_limits<WordIndex>::max()), + dedupe_(dedupe_mem, dedupe_mem_size, &dedupe_invalid_[0], DedupeHash(order), DedupeEquals(order)), + buffer_(new WordIndex[order - 1]), + block_size_(position.GetChain().BlockSize()) { + dedupe_.Clear(DedupeEntry::Construct(&dedupe_invalid_[0])); + assert(Dedupe::Size(position.GetChain().BlockSize() / position.GetChain().EntrySize(), kProbingMultiplier) == dedupe_mem_size); + if (order == 1) { + // Add special words. AdjustCounts is responsible if order != 1. + AddUnigramWord(kUNK); + AddUnigramWord(kBOS); + } + } + + ~Writer() { + block_->SetValidSize(reinterpret_cast<const uint8_t*>(gram_.begin()) - static_cast<const uint8_t*>(block_->Get())); + (++block_).Poison(); + } + + // Write context with a bunch of <s> + void StartSentence() { + for (WordIndex *i = gram_.begin(); i != gram_.end() - 1; ++i) { + *i = kBOS; + } + } + + void Append(WordIndex word) { + *(gram_.end() - 1) = word; + Dedupe::MutableIterator at; + bool found = dedupe_.FindOrInsert(DedupeEntry::Construct(gram_.begin()), at); + if (found) { + // Already present. + NGram already(at->key, gram_.Order()); + ++(already.Count()); + // Shift left by one. + memmove(gram_.begin(), gram_.begin() + 1, sizeof(WordIndex) * (gram_.Order() - 1)); + return; + } + // Complete the write. + gram_.Count() = 1; + // Prepare the next n-gram. + if (reinterpret_cast<uint8_t*>(gram_.begin()) + gram_.TotalSize() != static_cast<uint8_t*>(block_->Get()) + block_size_) { + NGram last(gram_); + gram_.NextInMemory(); + std::copy(last.begin() + 1, last.end(), gram_.begin()); + return; + } + // Block end. Need to store the context in a temporary buffer. + std::copy(gram_.begin() + 1, gram_.end(), buffer_.get()); + dedupe_.Clear(DedupeEntry::Construct(&dedupe_invalid_[0])); + block_->SetValidSize(block_size_); + gram_.ReBase((++block_)->Get()); + std::copy(buffer_.get(), buffer_.get() + gram_.Order() - 1, gram_.begin()); + } + + private: + void AddUnigramWord(WordIndex index) { + *gram_.begin() = index; + gram_.Count() = 0; + gram_.NextInMemory(); + if (gram_.Base() == static_cast<uint8_t*>(block_->Get()) + block_size_) { + block_->SetValidSize(block_size_); + gram_.ReBase((++block_)->Get()); + } + } + + util::stream::Link block_; + + NGram gram_; + + // This is the memory behind the invalid value in dedupe_. + std::vector<WordIndex> dedupe_invalid_; + // Hash table combiner implementation. + Dedupe dedupe_; + + // Small buffer to hold existing ngrams when shifting across a block boundary. + boost::scoped_array<WordIndex> buffer_; + + const std::size_t block_size_; +}; + +} // namespace + +float CorpusCount::DedupeMultiplier(std::size_t order) { + return kProbingMultiplier * static_cast<float>(sizeof(DedupeEntry)) / static_cast<float>(NGram::TotalSize(order)); +} + +CorpusCount::CorpusCount(util::FilePiece &from, int vocab_write, uint64_t &token_count, WordIndex &type_count, std::size_t entries_per_block) + : from_(from), vocab_write_(vocab_write), token_count_(token_count), type_count_(type_count), + dedupe_mem_size_(Dedupe::Size(entries_per_block, kProbingMultiplier)), + dedupe_mem_(util::MallocOrThrow(dedupe_mem_size_)) { + token_count_ = 0; + type_count_ = 0; +} + +void CorpusCount::Run(const util::stream::ChainPosition &position) { + UTIL_TIMER("(%w s) Counted n-grams\n"); + + VocabHandout vocab(vocab_write_); + const WordIndex end_sentence = vocab.Lookup("</s>"); + Writer writer(NGram::OrderFromSize(position.GetChain().EntrySize()), position, dedupe_mem_.get(), dedupe_mem_size_); + uint64_t count = 0; + StringPiece delimiters("\0\t\r ", 4); + try { + while(true) { + StringPiece line(from_.ReadLine()); + writer.StartSentence(); + for (util::TokenIter<util::AnyCharacter, true> w(line, delimiters); w; ++w) { + WordIndex word = vocab.Lookup(*w); + UTIL_THROW_IF(word <= 2, FormatLoadException, "Special word " << *w << " is not allowed in the corpus. I plan to support models containing <unk> in the future."); + writer.Append(word); + ++count; + } + writer.Append(end_sentence); + } + } catch (const util::EndOfFileException &e) {} + token_count_ = count; + type_count_ = vocab.Size(); +} + +} // namespace builder +} // namespace lm diff --git a/klm/lm/builder/corpus_count.hh b/klm/lm/builder/corpus_count.hh new file mode 100644 index 00000000..e255bad1 --- /dev/null +++ b/klm/lm/builder/corpus_count.hh @@ -0,0 +1,42 @@ +#ifndef LM_BUILDER_CORPUS_COUNT__ +#define LM_BUILDER_CORPUS_COUNT__ + +#include "lm/word_index.hh" +#include "util/scoped.hh" + +#include <cstddef> +#include <string> +#include <stdint.h> + +namespace util { +class FilePiece; +namespace stream { +class ChainPosition; +} // namespace stream +} // namespace util + +namespace lm { +namespace builder { + +class CorpusCount { + public: + // Memory usage will be DedupeMultipler(order) * block_size + total_chain_size + unknown vocab_hash_size + static float DedupeMultiplier(std::size_t order); + + CorpusCount(util::FilePiece &from, int vocab_write, uint64_t &token_count, WordIndex &type_count, std::size_t entries_per_block); + + void Run(const util::stream::ChainPosition &position); + + private: + util::FilePiece &from_; + int vocab_write_; + uint64_t &token_count_; + WordIndex &type_count_; + + std::size_t dedupe_mem_size_; + util::scoped_malloc dedupe_mem_; +}; + +} // namespace builder +} // namespace lm +#endif // LM_BUILDER_CORPUS_COUNT__ diff --git a/klm/lm/builder/corpus_count_test.cc b/klm/lm/builder/corpus_count_test.cc new file mode 100644 index 00000000..8d53ca9d --- /dev/null +++ b/klm/lm/builder/corpus_count_test.cc @@ -0,0 +1,76 @@ +#include "lm/builder/corpus_count.hh" + +#include "lm/builder/ngram.hh" +#include "lm/builder/ngram_stream.hh" + +#include "util/file.hh" +#include "util/file_piece.hh" +#include "util/tokenize_piece.hh" +#include "util/stream/chain.hh" +#include "util/stream/stream.hh" + +#define BOOST_TEST_MODULE CorpusCountTest +#include <boost/test/unit_test.hpp> + +namespace lm { namespace builder { namespace { + +#define Check(str, count) { \ + BOOST_REQUIRE(stream); \ + w = stream->begin(); \ + for (util::TokenIter<util::AnyCharacter, true> t(str, " "); t; ++t, ++w) { \ + BOOST_CHECK_EQUAL(*t, v[*w]); \ + } \ + BOOST_CHECK_EQUAL((uint64_t)count, stream->Count()); \ + ++stream; \ +} + +BOOST_AUTO_TEST_CASE(Short) { + util::scoped_fd input_file(util::MakeTemp("corpus_count_test_temp")); + const char input[] = "looking on a little more loin\non a little more loin\non foo little more loin\nbar\n\n"; + // Blocks of 10 are + // looking on a little more loin </s> on a little[duplicate] more[duplicate] loin[duplicate] </s>[duplicate] on[duplicate] foo + // little more loin </s> bar </s> </s> + + util::WriteOrThrow(input_file.get(), input, sizeof(input) - 1); + util::FilePiece input_piece(input_file.release(), "temp file"); + + util::stream::ChainConfig config; + config.entry_size = NGram::TotalSize(3); + config.total_memory = config.entry_size * 20; + config.block_count = 2; + + util::scoped_fd vocab(util::MakeTemp("corpus_count_test_vocab")); + + util::stream::Chain chain(config); + NGramStream stream; + uint64_t token_count; + WordIndex type_count; + CorpusCount counter(input_piece, vocab.get(), token_count, type_count, chain.BlockSize() / chain.EntrySize()); + chain >> boost::ref(counter) >> stream >> util::stream::kRecycle; + + const char *v[] = {"<unk>", "<s>", "</s>", "looking", "on", "a", "little", "more", "loin", "foo", "bar"}; + + WordIndex *w; + + Check("<s> <s> looking", 1); + Check("<s> looking on", 1); + Check("looking on a", 1); + Check("on a little", 2); + Check("a little more", 2); + Check("little more loin", 2); + Check("more loin </s>", 2); + Check("<s> <s> on", 2); + Check("<s> on a", 1); + Check("<s> on foo", 1); + Check("on foo little", 1); + Check("foo little more", 1); + Check("little more loin", 1); + Check("more loin </s>", 1); + Check("<s> <s> bar", 1); + Check("<s> bar </s>", 1); + Check("<s> <s> </s>", 1); + BOOST_CHECK(!stream); + BOOST_CHECK_EQUAL(sizeof(v) / sizeof(const char*), type_count); +} + +}}} // namespaces diff --git a/klm/lm/builder/discount.hh b/klm/lm/builder/discount.hh new file mode 100644 index 00000000..754fb20d --- /dev/null +++ b/klm/lm/builder/discount.hh @@ -0,0 +1,26 @@ +#ifndef BUILDER_DISCOUNT__ +#define BUILDER_DISCOUNT__ + +#include <algorithm> + +#include <inttypes.h> + +namespace lm { +namespace builder { + +struct Discount { + float amount[4]; + + float Get(uint64_t count) const { + return amount[std::min<uint64_t>(count, 3)]; + } + + float Apply(uint64_t count) const { + return static_cast<float>(count) - Get(count); + } +}; + +} // namespace builder +} // namespace lm + +#endif // BUILDER_DISCOUNT__ diff --git a/klm/lm/builder/header_info.hh b/klm/lm/builder/header_info.hh new file mode 100644 index 00000000..ccca1456 --- /dev/null +++ b/klm/lm/builder/header_info.hh @@ -0,0 +1,20 @@ +#ifndef LM_BUILDER_HEADER_INFO__ +#define LM_BUILDER_HEADER_INFO__ + +#include <string> +#include <stdint.h> + +// Some configuration info that is used to add +// comments to the beginning of an ARPA file +struct HeaderInfo { + const std::string input_file; + const uint64_t token_count; + + HeaderInfo(const std::string& input_file_in, uint64_t token_count_in) + : input_file(input_file_in), token_count(token_count_in) {} + + // TODO: Add smoothing type + // TODO: More info if multiple models were interpolated +}; + +#endif diff --git a/klm/lm/builder/initial_probabilities.cc b/klm/lm/builder/initial_probabilities.cc new file mode 100644 index 00000000..58b42a20 --- /dev/null +++ b/klm/lm/builder/initial_probabilities.cc @@ -0,0 +1,136 @@ +#include "lm/builder/initial_probabilities.hh" + +#include "lm/builder/discount.hh" +#include "lm/builder/ngram_stream.hh" +#include "lm/builder/sort.hh" +#include "util/file.hh" +#include "util/stream/chain.hh" +#include "util/stream/io.hh" +#include "util/stream/stream.hh" + +#include <vector> + +namespace lm { namespace builder { + +namespace { +struct BufferEntry { + // Gamma from page 20 of Chen and Goodman. + float gamma; + // \sum_w a(c w) for all w. + float denominator; +}; + +// Extract an array of gamma from an array of BufferEntry. +class OnlyGamma { + public: + void Run(const util::stream::ChainPosition &position) { + for (util::stream::Link block_it(position); block_it; ++block_it) { + float *out = static_cast<float*>(block_it->Get()); + const float *in = out; + const float *end = static_cast<const float*>(block_it->ValidEnd()); + for (out += 1, in += 2; in < end; out += 1, in += 2) { + *out = *in; + } + block_it->SetValidSize(block_it->ValidSize() / 2); + } + } +}; + +class AddRight { + public: + AddRight(const Discount &discount, const util::stream::ChainPosition &input) + : discount_(discount), input_(input) {} + + void Run(const util::stream::ChainPosition &output) { + NGramStream in(input_); + util::stream::Stream out(output); + + std::vector<WordIndex> previous(in->Order() - 1); + const std::size_t size = sizeof(WordIndex) * previous.size(); + for(; in; ++out) { + memcpy(&previous[0], in->begin(), size); + uint64_t denominator = 0; + uint64_t counts[4]; + memset(counts, 0, sizeof(counts)); + do { + denominator += in->Count(); + ++counts[std::min(in->Count(), static_cast<uint64_t>(3))]; + } while (++in && !memcmp(&previous[0], in->begin(), size)); + BufferEntry &entry = *reinterpret_cast<BufferEntry*>(out.Get()); + entry.denominator = static_cast<float>(denominator); + entry.gamma = 0.0; + for (unsigned i = 1; i <= 3; ++i) { + entry.gamma += discount_.Get(i) * static_cast<float>(counts[i]); + } + entry.gamma /= entry.denominator; + } + out.Poison(); + } + + private: + const Discount &discount_; + const util::stream::ChainPosition input_; +}; + +class MergeRight { + public: + MergeRight(bool interpolate_unigrams, const util::stream::ChainPosition &from_adder, const Discount &discount) + : interpolate_unigrams_(interpolate_unigrams), from_adder_(from_adder), discount_(discount) {} + + // calculate the initial probability of each n-gram (before order-interpolation) + // Run() gets invoked once for each order + void Run(const util::stream::ChainPosition &primary) { + util::stream::Stream summed(from_adder_); + + NGramStream grams(primary); + + // Without interpolation, the interpolation weight goes to <unk>. + if (grams->Order() == 1 && !interpolate_unigrams_) { + BufferEntry sums(*static_cast<const BufferEntry*>(summed.Get())); + assert(*grams->begin() == kUNK); + grams->Value().uninterp.prob = sums.gamma; + grams->Value().uninterp.gamma = 0.0; + while (++grams) { + grams->Value().uninterp.prob = discount_.Apply(grams->Count()) / sums.denominator; + grams->Value().uninterp.gamma = 0.0; + } + ++summed; + return; + } + + std::vector<WordIndex> previous(grams->Order() - 1); + const std::size_t size = sizeof(WordIndex) * previous.size(); + for (; grams; ++summed) { + memcpy(&previous[0], grams->begin(), size); + const BufferEntry &sums = *static_cast<const BufferEntry*>(summed.Get()); + do { + Payload &pay = grams->Value(); + pay.uninterp.prob = discount_.Apply(pay.count) / sums.denominator; + pay.uninterp.gamma = sums.gamma; + } while (++grams && !memcmp(&previous[0], grams->begin(), size)); + } + } + + private: + bool interpolate_unigrams_; + util::stream::ChainPosition from_adder_; + Discount discount_; +}; + +} // namespace + +void InitialProbabilities(const InitialProbabilitiesConfig &config, const std::vector<Discount> &discounts, Chains &primary, Chains &second_in, Chains &gamma_out) { + util::stream::ChainConfig gamma_config = config.adder_out; + gamma_config.entry_size = sizeof(BufferEntry); + for (size_t i = 0; i < primary.size(); ++i) { + util::stream::ChainPosition second(second_in[i].Add()); + second_in[i] >> util::stream::kRecycle; + gamma_out.push_back(gamma_config); + gamma_out[i] >> AddRight(discounts[i], second); + primary[i] >> MergeRight(config.interpolate_unigrams, gamma_out[i].Add(), discounts[i]); + // Don't bother with the OnlyGamma thread for something to discard. + if (i) gamma_out[i] >> OnlyGamma(); + } +} + +}} // namespaces diff --git a/klm/lm/builder/initial_probabilities.hh b/klm/lm/builder/initial_probabilities.hh new file mode 100644 index 00000000..626388eb --- /dev/null +++ b/klm/lm/builder/initial_probabilities.hh @@ -0,0 +1,34 @@ +#ifndef LM_BUILDER_INITIAL_PROBABILITIES__ +#define LM_BUILDER_INITIAL_PROBABILITIES__ + +#include "lm/builder/discount.hh" +#include "util/stream/config.hh" + +#include <vector> + +namespace lm { +namespace builder { +class Chains; + +struct InitialProbabilitiesConfig { + // These should be small buffers to keep the adder from getting too far ahead + util::stream::ChainConfig adder_in; + util::stream::ChainConfig adder_out; + // SRILM doesn't normally interpolate unigrams. + bool interpolate_unigrams; +}; + +/* Compute initial (uninterpolated) probabilities + * primary: the normal chain of n-grams. Incoming is context sorted adjusted + * counts. Outgoing has uninterpolated probabilities for use by Interpolate. + * second_in: a second copy of the primary input. Discard the output. + * gamma_out: Computed gamma values are output on these chains in suffix order. + * The values are bare floats and should be buffered for interpolation to + * use. + */ +void InitialProbabilities(const InitialProbabilitiesConfig &config, const std::vector<Discount> &discounts, Chains &primary, Chains &second_in, Chains &gamma_out); + +} // namespace builder +} // namespace lm + +#endif // LM_BUILDER_INITIAL_PROBABILITIES__ diff --git a/klm/lm/builder/interpolate.cc b/klm/lm/builder/interpolate.cc new file mode 100644 index 00000000..50026806 --- /dev/null +++ b/klm/lm/builder/interpolate.cc @@ -0,0 +1,65 @@ +#include "lm/builder/interpolate.hh" + +#include "lm/builder/joint_order.hh" +#include "lm/builder/multi_stream.hh" +#include "lm/builder/sort.hh" +#include "lm/lm_exception.hh" + +#include <assert.h> + +namespace lm { namespace builder { +namespace { + +class Callback { + public: + Callback(float uniform_prob, const ChainPositions &backoffs) : backoffs_(backoffs.size()), probs_(backoffs.size() + 2) { + probs_[0] = uniform_prob; + for (std::size_t i = 0; i < backoffs.size(); ++i) { + backoffs_.push_back(backoffs[i]); + } + } + + ~Callback() { + for (std::size_t i = 0; i < backoffs_.size(); ++i) { + if (backoffs_[i]) { + std::cerr << "Backoffs do not match for order " << (i + 1) << std::endl; + abort(); + } + } + } + + void Enter(unsigned order_minus_1, NGram &gram) { + Payload &pay = gram.Value(); + pay.complete.prob = pay.uninterp.prob + pay.uninterp.gamma * probs_[order_minus_1]; + probs_[order_minus_1 + 1] = pay.complete.prob; + pay.complete.prob = log10(pay.complete.prob); + // TODO: this is a hack to skip n-grams that don't appear as context. Pruning will require some different handling. + if (order_minus_1 < backoffs_.size() && *(gram.end() - 1) != kUNK && *(gram.end() - 1) != kEOS) { + pay.complete.backoff = log10(*static_cast<const float*>(backoffs_[order_minus_1].Get())); + ++backoffs_[order_minus_1]; + } else { + // Not a context. + pay.complete.backoff = 0.0; + } + } + + void Exit(unsigned, const NGram &) const {} + + private: + FixedArray<util::stream::Stream> backoffs_; + + std::vector<float> probs_; +}; +} // namespace + +Interpolate::Interpolate(uint64_t unigram_count, const ChainPositions &backoffs) + : uniform_prob_(1.0 / static_cast<float>(unigram_count - 1)), backoffs_(backoffs) {} + +// perform order-wise interpolation +void Interpolate::Run(const ChainPositions &positions) { + assert(positions.size() == backoffs_.size() + 1); + Callback callback(uniform_prob_, backoffs_); + JointOrder<Callback, SuffixOrder>(positions, callback); +} + +}} // namespaces diff --git a/klm/lm/builder/interpolate.hh b/klm/lm/builder/interpolate.hh new file mode 100644 index 00000000..9268d404 --- /dev/null +++ b/klm/lm/builder/interpolate.hh @@ -0,0 +1,27 @@ +#ifndef LM_BUILDER_INTERPOLATE__ +#define LM_BUILDER_INTERPOLATE__ + +#include <stdint.h> + +#include "lm/builder/multi_stream.hh" + +namespace lm { namespace builder { + +/* Interpolate step. + * Input: suffix sorted n-grams with (p_uninterpolated, gamma) from + * InitialProbabilities. + * Output: suffix sorted n-grams with complete probability + */ +class Interpolate { + public: + explicit Interpolate(uint64_t unigram_count, const ChainPositions &backoffs); + + void Run(const ChainPositions &positions); + + private: + float uniform_prob_; + ChainPositions backoffs_; +}; + +}} // namespaces +#endif // LM_BUILDER_INTERPOLATE__ diff --git a/klm/lm/builder/joint_order.hh b/klm/lm/builder/joint_order.hh new file mode 100644 index 00000000..b5620144 --- /dev/null +++ b/klm/lm/builder/joint_order.hh @@ -0,0 +1,43 @@ +#ifndef LM_BUILDER_JOINT_ORDER__ +#define LM_BUILDER_JOINT_ORDER__ + +#include "lm/builder/multi_stream.hh" +#include "lm/lm_exception.hh" + +#include <string.h> + +namespace lm { namespace builder { + +template <class Callback, class Compare> void JointOrder(const ChainPositions &positions, Callback &callback) { + // Allow matching to reference streams[-1]. + NGramStreams streams_with_dummy; + streams_with_dummy.InitWithDummy(positions); + NGramStream *streams = streams_with_dummy.begin() + 1; + + unsigned int order; + for (order = 0; order < positions.size() && streams[order]; ++order) {} + assert(order); // should always have <unk>. + unsigned int current = 0; + while (true) { + // Does the context match the lower one? + if (!memcmp(streams[static_cast<int>(current) - 1]->begin(), streams[current]->begin() + Compare::kMatchOffset, sizeof(WordIndex) * current)) { + callback.Enter(current, *streams[current]); + // Transition to looking for extensions. + if (++current < order) continue; + } + // No extension left. + while(true) { + assert(current > 0); + --current; + callback.Exit(current, *streams[current]); + if (++streams[current]) break; + UTIL_THROW_IF(order != current + 1, FormatLoadException, "Detected n-gram without matching suffix"); + order = current; + if (!order) return; + } + } +} + +}} // namespaces + +#endif // LM_BUILDER_JOINT_ORDER__ diff --git a/klm/lm/builder/main.cc b/klm/lm/builder/main.cc new file mode 100644 index 00000000..90b9dca2 --- /dev/null +++ b/klm/lm/builder/main.cc @@ -0,0 +1,94 @@ +#include "lm/builder/pipeline.hh" +#include "util/file.hh" +#include "util/file_piece.hh" +#include "util/usage.hh" + +#include <iostream> + +#include <boost/program_options.hpp> + +namespace { +class SizeNotify { + public: + SizeNotify(std::size_t &out) : behind_(out) {} + + void operator()(const std::string &from) { + behind_ = util::ParseSize(from); + } + + private: + std::size_t &behind_; +}; + +boost::program_options::typed_value<std::string> *SizeOption(std::size_t &to, const char *default_value) { + return boost::program_options::value<std::string>()->notifier(SizeNotify(to))->default_value(default_value); +} + +} // namespace + +int main(int argc, char *argv[]) { + try { + namespace po = boost::program_options; + po::options_description options("Language model building options"); + lm::builder::PipelineConfig pipeline; + + options.add_options() + ("order,o", po::value<std::size_t>(&pipeline.order)->required(), "Order of the model") + ("interpolate_unigrams", po::bool_switch(&pipeline.initial_probs.interpolate_unigrams), "Interpolate the unigrams (default: emulate SRILM by not interpolating)") + ("temp_prefix,T", po::value<std::string>(&pipeline.sort.temp_prefix)->default_value("/tmp/lm"), "Temporary file prefix") + ("memory,S", SizeOption(pipeline.sort.total_memory, util::GuessPhysicalMemory() ? "80%" : "1G"), "Sorting memory") + ("vocab_memory", SizeOption(pipeline.assume_vocab_hash_size, "50M"), "Assume that the vocabulary hash table will use this much memory for purposes of calculating total memory in the count step") + ("minimum_block", SizeOption(pipeline.minimum_block, "8K"), "Minimum block size to allow") + ("sort_block", SizeOption(pipeline.sort.buffer_size, "64M"), "Size of IO operations for sort (determines arity)") + ("block_count", po::value<std::size_t>(&pipeline.block_count)->default_value(2), "Block count (per order)") + ("vocab_file", po::value<std::string>(&pipeline.vocab_file)->default_value(""), "Location to write vocabulary file") + ("verbose_header", po::bool_switch(&pipeline.verbose_header), "Add a verbose header to the ARPA file that includes information such as token count, smoothing type, etc."); + if (argc == 1) { + std::cerr << + "Builds unpruned language models with modified Kneser-Ney smoothing.\n\n" + "Please cite:\n" + "@inproceedings{kenlm,\n" + "author = {Kenneth Heafield},\n" + "title = {{KenLM}: Faster and Smaller Language Model Queries},\n" + "booktitle = {Proceedings of the Sixth Workshop on Statistical Machine Translation},\n" + "month = {July}, year={2011},\n" + "address = {Edinburgh, UK},\n" + "publisher = {Association for Computational Linguistics},\n" + "}\n\n" + "Provide the corpus on stdin. The ARPA file will be written to stdout. Order of\n" + "the model (-o) is the only mandatory option. As this is an on-disk program,\n" + "setting the temporary file location (-T) and sorting memory (-S) is recommended.\n\n" + "Memory sizes are specified like GNU sort: a number followed by a unit character.\n" + "Valid units are \% for percentage of memory (supported platforms only) and (in\n" + "increasing powers of 1024): b, K, M, G, T, P, E, Z, Y. Default is K (*1024).\n\n"; + std::cerr << options << std::endl; + return 1; + } + po::variables_map vm; + po::store(po::parse_command_line(argc, argv, options), vm); + po::notify(vm); + + util::NormalizeTempPrefix(pipeline.sort.temp_prefix); + + lm::builder::InitialProbabilitiesConfig &initial = pipeline.initial_probs; + // TODO: evaluate options for these. + initial.adder_in.total_memory = 32768; + initial.adder_in.block_count = 2; + initial.adder_out.total_memory = 32768; + initial.adder_out.block_count = 2; + pipeline.read_backoffs = initial.adder_out; + + // Read from stdin + try { + lm::builder::Pipeline(pipeline, 0, 1); + } catch (const util::MallocException &e) { + std::cerr << e.what() << std::endl; + std::cerr << "Try rerunning with a more conservative -S setting than " << vm["memory"].as<std::string>() << std::endl; + return 1; + } + util::PrintUsage(std::cerr); + } catch (const std::exception &e) { + std::cerr << e.what() << std::endl; + return 1; + } +} diff --git a/klm/lm/builder/multi_stream.hh b/klm/lm/builder/multi_stream.hh new file mode 100644 index 00000000..707a98c7 --- /dev/null +++ b/klm/lm/builder/multi_stream.hh @@ -0,0 +1,180 @@ +#ifndef LM_BUILDER_MULTI_STREAM__ +#define LM_BUILDER_MULTI_STREAM__ + +#include "lm/builder/ngram_stream.hh" +#include "util/scoped.hh" +#include "util/stream/chain.hh" + +#include <cstddef> +#include <new> + +#include <assert.h> +#include <stdlib.h> + +namespace lm { namespace builder { + +template <class T> class FixedArray { + public: + explicit FixedArray(std::size_t count) { + Init(count); + } + + FixedArray() : newed_end_(NULL) {} + + void Init(std::size_t count) { + assert(!block_.get()); + block_.reset(malloc(sizeof(T) * count)); + if (!block_.get()) throw std::bad_alloc(); + newed_end_ = begin(); + } + + FixedArray(const FixedArray &from) { + std::size_t size = from.newed_end_ - static_cast<const T*>(from.block_.get()); + Init(size); + for (std::size_t i = 0; i < size; ++i) { + new(end()) T(from[i]); + Constructed(); + } + } + + ~FixedArray() { clear(); } + + T *begin() { return static_cast<T*>(block_.get()); } + const T *begin() const { return static_cast<const T*>(block_.get()); } + // Always call Constructed after successful completion of new. + T *end() { return newed_end_; } + const T *end() const { return newed_end_; } + + T &back() { return *(end() - 1); } + const T &back() const { return *(end() - 1); } + + std::size_t size() const { return end() - begin(); } + bool empty() const { return begin() == end(); } + + T &operator[](std::size_t i) { return begin()[i]; } + const T &operator[](std::size_t i) const { return begin()[i]; } + + template <class C> void push_back(const C &c) { + new (end()) T(c); + Constructed(); + } + + void clear() { + for (T *i = begin(); i != end(); ++i) + i->~T(); + newed_end_ = begin(); + } + + protected: + void Constructed() { + ++newed_end_; + } + + private: + util::scoped_malloc block_; + + T *newed_end_; +}; + +class Chains; + +class ChainPositions : public FixedArray<util::stream::ChainPosition> { + public: + ChainPositions() {} + + void Init(Chains &chains); + + explicit ChainPositions(Chains &chains) { + Init(chains); + } +}; + +class Chains : public FixedArray<util::stream::Chain> { + private: + template <class T, void (T::*ptr)(const ChainPositions &) = &T::Run> struct CheckForRun { + typedef Chains type; + }; + + public: + explicit Chains(std::size_t limit) : FixedArray<util::stream::Chain>(limit) {} + + template <class Worker> typename CheckForRun<Worker>::type &operator>>(const Worker &worker) { + threads_.push_back(new util::stream::Thread(ChainPositions(*this), worker)); + return *this; + } + + template <class Worker> typename CheckForRun<Worker>::type &operator>>(const boost::reference_wrapper<Worker> &worker) { + threads_.push_back(new util::stream::Thread(ChainPositions(*this), worker)); + return *this; + } + + Chains &operator>>(const util::stream::Recycler &recycler) { + for (util::stream::Chain *i = begin(); i != end(); ++i) + *i >> recycler; + return *this; + } + + void Wait(bool release_memory = true) { + threads_.clear(); + for (util::stream::Chain *i = begin(); i != end(); ++i) { + i->Wait(release_memory); + } + } + + private: + boost::ptr_vector<util::stream::Thread> threads_; + + Chains(const Chains &); + void operator=(const Chains &); +}; + +inline void ChainPositions::Init(Chains &chains) { + FixedArray<util::stream::ChainPosition>::Init(chains.size()); + for (util::stream::Chain *i = chains.begin(); i != chains.end(); ++i) { + new (end()) util::stream::ChainPosition(i->Add()); Constructed(); + } +} + +inline Chains &operator>>(Chains &chains, ChainPositions &positions) { + positions.Init(chains); + return chains; +} + +class NGramStreams : public FixedArray<NGramStream> { + public: + NGramStreams() {} + + // This puts a dummy NGramStream at the beginning (useful to algorithms that need to reference something at the beginning). + void InitWithDummy(const ChainPositions &positions) { + FixedArray<NGramStream>::Init(positions.size() + 1); + new (end()) NGramStream(); Constructed(); + for (const util::stream::ChainPosition *i = positions.begin(); i != positions.end(); ++i) { + push_back(*i); + } + } + + // Limit restricts to positions[0,limit) + void Init(const ChainPositions &positions, std::size_t limit) { + FixedArray<NGramStream>::Init(limit); + for (const util::stream::ChainPosition *i = positions.begin(); i != positions.begin() + limit; ++i) { + push_back(*i); + } + } + void Init(const ChainPositions &positions) { + Init(positions, positions.size()); + } + + NGramStreams(const ChainPositions &positions) { + Init(positions); + } +}; + +inline Chains &operator>>(Chains &chains, NGramStreams &streams) { + ChainPositions positions; + chains >> positions; + streams.Init(positions); + return chains; +} + +}} // namespaces +#endif // LM_BUILDER_MULTI_STREAM__ diff --git a/klm/lm/builder/ngram.hh b/klm/lm/builder/ngram.hh new file mode 100644 index 00000000..2984ed0b --- /dev/null +++ b/klm/lm/builder/ngram.hh @@ -0,0 +1,84 @@ +#ifndef LM_BUILDER_NGRAM__ +#define LM_BUILDER_NGRAM__ + +#include "lm/weights.hh" +#include "lm/word_index.hh" + +#include <cstddef> + +#include <assert.h> +#include <stdint.h> +#include <string.h> + +namespace lm { +namespace builder { + +struct Uninterpolated { + float prob; // Uninterpolated probability. + float gamma; // Interpolation weight for lower order. +}; + +union Payload { + uint64_t count; + Uninterpolated uninterp; + ProbBackoff complete; +}; + +class NGram { + public: + NGram(void *begin, std::size_t order) + : begin_(static_cast<WordIndex*>(begin)), end_(begin_ + order) {} + + const uint8_t *Base() const { return reinterpret_cast<const uint8_t*>(begin_); } + uint8_t *Base() { return reinterpret_cast<uint8_t*>(begin_); } + + void ReBase(void *to) { + std::size_t difference = end_ - begin_; + begin_ = reinterpret_cast<WordIndex*>(to); + end_ = begin_ + difference; + } + + // Would do operator++ but that can get confusing for a stream. + void NextInMemory() { + ReBase(&Value() + 1); + } + + // Lower-case in deference to STL. + const WordIndex *begin() const { return begin_; } + WordIndex *begin() { return begin_; } + const WordIndex *end() const { return end_; } + WordIndex *end() { return end_; } + + const Payload &Value() const { return *reinterpret_cast<const Payload *>(end_); } + Payload &Value() { return *reinterpret_cast<Payload *>(end_); } + + uint64_t &Count() { return Value().count; } + const uint64_t Count() const { return Value().count; } + + std::size_t Order() const { return end_ - begin_; } + + static std::size_t TotalSize(std::size_t order) { + return order * sizeof(WordIndex) + sizeof(Payload); + } + std::size_t TotalSize() const { + // Compiler should optimize this. + return TotalSize(Order()); + } + static std::size_t OrderFromSize(std::size_t size) { + std::size_t ret = (size - sizeof(Payload)) / sizeof(WordIndex); + assert(size == TotalSize(ret)); + return ret; + } + + private: + WordIndex *begin_, *end_; +}; + +const WordIndex kUNK = 0; +const WordIndex kBOS = 1; +const WordIndex kEOS = 2; + +} // namespace builder +} // namespace lm + +#endif // LM_BUILDER_NGRAM__ diff --git a/klm/lm/builder/ngram_stream.hh b/klm/lm/builder/ngram_stream.hh new file mode 100644 index 00000000..3c994664 --- /dev/null +++ b/klm/lm/builder/ngram_stream.hh @@ -0,0 +1,55 @@ +#ifndef LM_BUILDER_NGRAM_STREAM__ +#define LM_BUILDER_NGRAM_STREAM__ + +#include "lm/builder/ngram.hh" +#include "util/stream/chain.hh" +#include "util/stream/stream.hh" + +#include <cstddef> + +namespace lm { namespace builder { + +class NGramStream { + public: + NGramStream() : gram_(NULL, 0) {} + + NGramStream(const util::stream::ChainPosition &position) : gram_(NULL, 0) { + Init(position); + } + + void Init(const util::stream::ChainPosition &position) { + stream_.Init(position); + gram_ = NGram(stream_.Get(), NGram::OrderFromSize(position.GetChain().EntrySize())); + } + + NGram &operator*() { return gram_; } + const NGram &operator*() const { return gram_; } + + NGram *operator->() { return &gram_; } + const NGram *operator->() const { return &gram_; } + + void *Get() { return stream_.Get(); } + const void *Get() const { return stream_.Get(); } + + operator bool() const { return stream_; } + bool operator!() const { return !stream_; } + void Poison() { stream_.Poison(); } + + NGramStream &operator++() { + ++stream_; + gram_.ReBase(stream_.Get()); + return *this; + } + + private: + NGram gram_; + util::stream::Stream stream_; +}; + +inline util::stream::Chain &operator>>(util::stream::Chain &chain, NGramStream &str) { + str.Init(chain.Add()); + return chain; +} + +}} // namespaces +#endif // LM_BUILDER_NGRAM_STREAM__ diff --git a/klm/lm/builder/pipeline.cc b/klm/lm/builder/pipeline.cc new file mode 100644 index 00000000..14a1f721 --- /dev/null +++ b/klm/lm/builder/pipeline.cc @@ -0,0 +1,320 @@ +#include "lm/builder/pipeline.hh" + +#include "lm/builder/adjust_counts.hh" +#include "lm/builder/corpus_count.hh" +#include "lm/builder/initial_probabilities.hh" +#include "lm/builder/interpolate.hh" +#include "lm/builder/print.hh" +#include "lm/builder/sort.hh" + +#include "lm/sizes.hh" + +#include "util/exception.hh" +#include "util/file.hh" +#include "util/stream/io.hh" + +#include <algorithm> +#include <iostream> +#include <vector> + +namespace lm { namespace builder { + +namespace { +void PrintStatistics(const std::vector<uint64_t> &counts, const std::vector<Discount> &discounts) { + std::cerr << "Statistics:\n"; + for (size_t i = 0; i < counts.size(); ++i) { + std::cerr << (i + 1) << ' ' << counts[i]; + for (size_t d = 1; d <= 3; ++d) + std::cerr << " D" << d << (d == 3 ? "+=" : "=") << discounts[i].amount[d]; + std::cerr << '\n'; + } +} + +class Master { + public: + explicit Master(const PipelineConfig &config) + : config_(config), chains_(config.order), files_(config.order) { + config_.minimum_block = std::max(NGram::TotalSize(config_.order), config_.minimum_block); + } + + const PipelineConfig &Config() const { return config_; } + + Chains &MutableChains() { return chains_; } + + template <class T> Master &operator>>(const T &worker) { + chains_ >> worker; + return *this; + } + + // This takes the (partially) sorted ngrams and sets up for adjusted counts. + void InitForAdjust(util::stream::Sort<SuffixOrder, AddCombiner> &ngrams, WordIndex types) { + const std::size_t each_order_min = config_.minimum_block * config_.block_count; + // We know how many unigrams there are. Don't allocate more than needed to them. + const std::size_t min_chains = (config_.order - 1) * each_order_min + + std::min(types * NGram::TotalSize(1), each_order_min); + // Do merge sort with calculated laziness. + const std::size_t merge_using = ngrams.Merge(std::min(config_.TotalMemory() - min_chains, ngrams.DefaultLazy())); + + std::vector<uint64_t> count_bounds(1, types); + CreateChains(config_.TotalMemory() - merge_using, count_bounds); + ngrams.Output(chains_.back(), merge_using); + + // Setup unigram file. + files_.push_back(util::MakeTemp(config_.TempPrefix())); + } + + // For initial probabilities, but this is generic. + void SortAndReadTwice(const std::vector<uint64_t> &counts, Sorts<ContextOrder> &sorts, Chains &second, util::stream::ChainConfig second_config) { + // Do merge first before allocating chain memory. + for (std::size_t i = 1; i < config_.order; ++i) { + sorts[i - 1].Merge(0); + } + // There's no lazy merge, so just divide memory amongst the chains. + CreateChains(config_.TotalMemory(), counts); + chains_.back().ActivateProgress(); + chains_[0] >> files_[0].Source(); + second_config.entry_size = NGram::TotalSize(1); + second.push_back(second_config); + second.back() >> files_[0].Source(); + for (std::size_t i = 1; i < config_.order; ++i) { + util::scoped_fd fd(sorts[i - 1].StealCompleted()); + chains_[i].SetProgressTarget(util::SizeOrThrow(fd.get())); + chains_[i] >> util::stream::PRead(util::DupOrThrow(fd.get()), true); + second_config.entry_size = NGram::TotalSize(i + 1); + second.push_back(second_config); + second.back() >> util::stream::PRead(fd.release(), true); + } + } + + // There is no sort after this, so go for broke on lazy merging. + template <class Compare> void MaximumLazyInput(const std::vector<uint64_t> &counts, Sorts<Compare> &sorts) { + // Determine the minimum we can use for all the chains. + std::size_t min_chains = 0; + for (std::size_t i = 0; i < config_.order; ++i) { + min_chains += std::min(counts[i] * NGram::TotalSize(i + 1), static_cast<uint64_t>(config_.minimum_block)); + } + std::size_t for_merge = min_chains > config_.TotalMemory() ? 0 : (config_.TotalMemory() - min_chains); + std::vector<std::size_t> laziness; + // Prioritize longer n-grams. + for (util::stream::Sort<SuffixOrder> *i = sorts.end() - 1; i >= sorts.begin(); --i) { + laziness.push_back(i->Merge(for_merge)); + assert(for_merge >= laziness.back()); + for_merge -= laziness.back(); + } + std::reverse(laziness.begin(), laziness.end()); + + CreateChains(for_merge + min_chains, counts); + chains_.back().ActivateProgress(); + chains_[0] >> files_[0].Source(); + for (std::size_t i = 1; i < config_.order; ++i) { + sorts[i - 1].Output(chains_[i], laziness[i - 1]); + } + } + + void BufferFinal(const std::vector<uint64_t> &counts) { + chains_[0] >> files_[0].Sink(); + for (std::size_t i = 1; i < config_.order; ++i) { + files_.push_back(util::MakeTemp(config_.TempPrefix())); + chains_[i] >> files_[i].Sink(); + } + chains_.Wait(true); + // Use less memory. Because we can. + CreateChains(std::min(config_.sort.buffer_size * config_.order, config_.TotalMemory()), counts); + for (std::size_t i = 0; i < config_.order; ++i) { + chains_[i] >> files_[i].Source(); + } + } + + template <class Compare> void SetupSorts(Sorts<Compare> &sorts) { + sorts.Init(config_.order - 1); + // Unigrams don't get sorted because their order is always the same. + chains_[0] >> files_[0].Sink(); + for (std::size_t i = 1; i < config_.order; ++i) { + sorts.push_back(chains_[i], config_.sort, Compare(i + 1)); + } + chains_.Wait(true); + } + + private: + // Create chains, allocating memory to them. Totally heuristic. Count + // bounds are upper bounds on the counts or not present. + void CreateChains(std::size_t remaining_mem, const std::vector<uint64_t> &count_bounds) { + std::vector<std::size_t> assignments; + assignments.reserve(config_.order); + // Start by assigning maximum memory usage (to be refined later). + for (std::size_t i = 0; i < count_bounds.size(); ++i) { + assignments.push_back(static_cast<std::size_t>(std::min( + static_cast<uint64_t>(remaining_mem), + count_bounds[i] * static_cast<uint64_t>(NGram::TotalSize(i + 1))))); + } + assignments.resize(config_.order, remaining_mem); + + // Now we know how much memory everybody wants. How much will they get? + // Proportional to this. + std::vector<float> portions; + // Indices of orders that have yet to be assigned. + std::vector<std::size_t> unassigned; + for (std::size_t i = 0; i < config_.order; ++i) { + portions.push_back(static_cast<float>((i+1) * NGram::TotalSize(i+1))); + unassigned.push_back(i); + } + /*If somebody doesn't eat their full dinner, give it to the rest of the + * family. Then somebody else might not eat their full dinner etc. Ends + * when everybody unassigned is hungry. + */ + float sum; + bool found_more; + std::vector<std::size_t> block_count(config_.order); + do { + sum = 0.0; + for (std::size_t i = 0; i < unassigned.size(); ++i) { + sum += portions[unassigned[i]]; + } + found_more = false; + // If the proportional assignment is more than needed, give it just what it needs. + for (std::vector<std::size_t>::iterator i = unassigned.begin(); i != unassigned.end();) { + if (assignments[*i] <= remaining_mem * (portions[*i] / sum)) { + remaining_mem -= assignments[*i]; + block_count[*i] = 1; + i = unassigned.erase(i); + found_more = true; + } else { + ++i; + } + } + } while (found_more); + for (std::vector<std::size_t>::iterator i = unassigned.begin(); i != unassigned.end(); ++i) { + assignments[*i] = remaining_mem * (portions[*i] / sum); + block_count[*i] = config_.block_count; + } + chains_.clear(); + std::cerr << "Chain sizes:"; + for (std::size_t i = 0; i < config_.order; ++i) { + std::cerr << ' ' << (i+1) << ":" << assignments[i]; + chains_.push_back(util::stream::ChainConfig(NGram::TotalSize(i + 1), block_count[i], assignments[i])); + } + std::cerr << std::endl; + } + + PipelineConfig config_; + + Chains chains_; + // Often only unigrams, but sometimes all orders. + FixedArray<util::stream::FileBuffer> files_; +}; + +void CountText(int text_file /* input */, int vocab_file /* output */, Master &master, uint64_t &token_count, std::string &text_file_name) { + const PipelineConfig &config = master.Config(); + std::cerr << "=== 1/5 Counting and sorting n-grams ===" << std::endl; + + UTIL_THROW_IF(config.TotalMemory() < config.assume_vocab_hash_size, util::Exception, "Vocab hash size estimate " << config.assume_vocab_hash_size << " exceeds total memory " << config.TotalMemory()); + std::size_t memory_for_chain = + // This much memory to work with after vocab hash table. + static_cast<float>(config.TotalMemory() - config.assume_vocab_hash_size) / + // Solve for block size including the dedupe multiplier for one block. + (static_cast<float>(config.block_count) + CorpusCount::DedupeMultiplier(config.order)) * + // Chain likes memory expressed in terms of total memory. + static_cast<float>(config.block_count); + util::stream::Chain chain(util::stream::ChainConfig(NGram::TotalSize(config.order), config.block_count, memory_for_chain)); + + WordIndex type_count; + util::FilePiece text(text_file, NULL, &std::cerr); + text_file_name = text.FileName(); + CorpusCount counter(text, vocab_file, token_count, type_count, chain.BlockSize() / chain.EntrySize()); + chain >> boost::ref(counter); + + util::stream::Sort<SuffixOrder, AddCombiner> sorter(chain, config.sort, SuffixOrder(config.order), AddCombiner()); + chain.Wait(true); + std::cerr << "=== 2/5 Calculating and sorting adjusted counts ===" << std::endl; + master.InitForAdjust(sorter, type_count); +} + +void InitialProbabilities(const std::vector<uint64_t> &counts, const std::vector<Discount> &discounts, Master &master, Sorts<SuffixOrder> &primary, FixedArray<util::stream::FileBuffer> &gammas) { + const PipelineConfig &config = master.Config(); + Chains second(config.order); + + { + Sorts<ContextOrder> sorts; + master.SetupSorts(sorts); + PrintStatistics(counts, discounts); + lm::ngram::ShowSizes(counts); + std::cerr << "=== 3/5 Calculating and sorting initial probabilities ===" << std::endl; + master.SortAndReadTwice(counts, sorts, second, config.initial_probs.adder_in); + } + + Chains gamma_chains(config.order); + InitialProbabilities(config.initial_probs, discounts, master.MutableChains(), second, gamma_chains); + // Don't care about gamma for 0. + gamma_chains[0] >> util::stream::kRecycle; + gammas.Init(config.order - 1); + for (std::size_t i = 1; i < config.order; ++i) { + gammas.push_back(util::MakeTemp(config.TempPrefix())); + gamma_chains[i] >> gammas[i - 1].Sink(); + } + // Has to be done here due to gamma_chains scope. + master.SetupSorts(primary); +} + +void InterpolateProbabilities(const std::vector<uint64_t> &counts, Master &master, Sorts<SuffixOrder> &primary, FixedArray<util::stream::FileBuffer> &gammas) { + std::cerr << "=== 4/5 Calculating and writing order-interpolated probabilities ===" << std::endl; + const PipelineConfig &config = master.Config(); + master.MaximumLazyInput(counts, primary); + + Chains gamma_chains(config.order - 1); + util::stream::ChainConfig read_backoffs(config.read_backoffs); + read_backoffs.entry_size = sizeof(float); + for (std::size_t i = 0; i < config.order - 1; ++i) { + gamma_chains.push_back(read_backoffs); + gamma_chains.back() >> gammas[i].Source(); + } + master >> Interpolate(counts[0], ChainPositions(gamma_chains)); + gamma_chains >> util::stream::kRecycle; + master.BufferFinal(counts); +} + +} // namespace + +void Pipeline(PipelineConfig config, int text_file, int out_arpa) { + // Some fail-fast sanity checks. + if (config.sort.buffer_size * 4 > config.TotalMemory()) { + config.sort.buffer_size = config.TotalMemory() / 4; + std::cerr << "Warning: changing sort block size to " << config.sort.buffer_size << " bytes due to low total memory." << std::endl; + } + if (config.minimum_block < NGram::TotalSize(config.order)) { + config.minimum_block = NGram::TotalSize(config.order); + std::cerr << "Warning: raising minimum block to " << config.minimum_block << " to fit an ngram in every block." << std::endl; + } + UTIL_THROW_IF(config.sort.buffer_size < config.minimum_block, util::Exception, "Sort block size " << config.sort.buffer_size << " is below the minimum block size " << config.minimum_block << "."); + UTIL_THROW_IF(config.TotalMemory() < config.minimum_block * config.order * config.block_count, util::Exception, + "Not enough memory to fit " << (config.order * config.block_count) << " blocks with minimum size " << config.minimum_block << ". Increase memory to " << (config.minimum_block * config.order * config.block_count) << " bytes or decrease the minimum block size."); + + UTIL_TIMER("(%w s) Total wall time elapsed\n"); + Master master(config); + + util::scoped_fd vocab_file(config.vocab_file.empty() ? + util::MakeTemp(config.TempPrefix()) : + util::CreateOrThrow(config.vocab_file.c_str())); + uint64_t token_count; + std::string text_file_name; + CountText(text_file, vocab_file.get(), master, token_count, text_file_name); + + std::vector<uint64_t> counts; + std::vector<Discount> discounts; + master >> AdjustCounts(counts, discounts); + + { + FixedArray<util::stream::FileBuffer> gammas; + Sorts<SuffixOrder> primary; + InitialProbabilities(counts, discounts, master, primary, gammas); + InterpolateProbabilities(counts, master, primary, gammas); + } + + std::cerr << "=== 5/5 Writing ARPA model ===" << std::endl; + VocabReconstitute vocab(vocab_file.get()); + UTIL_THROW_IF(vocab.Size() != counts[0], util::Exception, "Vocab words don't match up. Is there a null byte in the input?"); + HeaderInfo header_info(text_file_name, token_count); + master >> PrintARPA(vocab, counts, (config.verbose_header ? &header_info : NULL), out_arpa) >> util::stream::kRecycle; + master.MutableChains().Wait(true); +} + +}} // namespaces diff --git a/klm/lm/builder/pipeline.hh b/klm/lm/builder/pipeline.hh new file mode 100644 index 00000000..f1d6c5f6 --- /dev/null +++ b/klm/lm/builder/pipeline.hh @@ -0,0 +1,40 @@ +#ifndef LM_BUILDER_PIPELINE__ +#define LM_BUILDER_PIPELINE__ + +#include "lm/builder/initial_probabilities.hh" +#include "lm/builder/header_info.hh" +#include "util/stream/config.hh" +#include "util/file_piece.hh" + +#include <string> +#include <cstddef> + +namespace lm { namespace builder { + +struct PipelineConfig { + std::size_t order; + std::string vocab_file; + util::stream::SortConfig sort; + InitialProbabilitiesConfig initial_probs; + util::stream::ChainConfig read_backoffs; + bool verbose_header; + + // Amount of memory to assume that the vocabulary hash table will use. This + // is subtracted from total memory for CorpusCount. + std::size_t assume_vocab_hash_size; + + // Minimum block size to tolerate. + std::size_t minimum_block; + + // Number of blocks to use. This will be overridden to 1 if everything fits. + std::size_t block_count; + + const std::string &TempPrefix() const { return sort.temp_prefix; } + std::size_t TotalMemory() const { return sort.total_memory; } +}; + +// Takes ownership of text_file. +void Pipeline(PipelineConfig config, int text_file, int out_arpa); + +}} // namespaces +#endif // LM_BUILDER_PIPELINE__ diff --git a/klm/lm/builder/print.cc b/klm/lm/builder/print.cc new file mode 100644 index 00000000..b0323221 --- /dev/null +++ b/klm/lm/builder/print.cc @@ -0,0 +1,135 @@ +#include "lm/builder/print.hh" + +#include "util/double-conversion/double-conversion.h" +#include "util/double-conversion/utils.h" +#include "util/file.hh" +#include "util/mmap.hh" +#include "util/scoped.hh" +#include "util/stream/timer.hh" + +#define BOOST_LEXICAL_CAST_ASSUME_C_LOCALE +#include <boost/lexical_cast.hpp> + +#include <sstream> + +#include <string.h> + +namespace lm { namespace builder { + +VocabReconstitute::VocabReconstitute(int fd) { + uint64_t size = util::SizeOrThrow(fd); + util::MapRead(util::POPULATE_OR_READ, fd, 0, size, memory_); + const char *const start = static_cast<const char*>(memory_.get()); + const char *i; + for (i = start; i != start + size; i += strlen(i) + 1) { + map_.push_back(i); + } + // Last one for LookupPiece. + map_.push_back(i); +} + +namespace { +class OutputManager { + public: + static const std::size_t kOutBuf = 1048576; + + // Does not take ownership of out. + explicit OutputManager(int out) + : buf_(util::MallocOrThrow(kOutBuf)), + builder_(static_cast<char*>(buf_.get()), kOutBuf), + // Mostly the default but with inf instead. And no flags. + convert_(double_conversion::DoubleToStringConverter::NO_FLAGS, "inf", "NaN", 'e', -6, 21, 6, 0), + fd_(out) {} + + ~OutputManager() { + Flush(); + } + + OutputManager &operator<<(float value) { + // Odd, but this is the largest number found in the comments. + EnsureRemaining(double_conversion::DoubleToStringConverter::kMaxPrecisionDigits + 8); + convert_.ToShortestSingle(value, &builder_); + return *this; + } + + OutputManager &operator<<(StringPiece str) { + if (str.size() > kOutBuf) { + Flush(); + util::WriteOrThrow(fd_, str.data(), str.size()); + } else { + EnsureRemaining(str.size()); + builder_.AddSubstring(str.data(), str.size()); + } + return *this; + } + + // Inefficient! + OutputManager &operator<<(unsigned val) { + return *this << boost::lexical_cast<std::string>(val); + } + + OutputManager &operator<<(char c) { + EnsureRemaining(1); + builder_.AddCharacter(c); + return *this; + } + + void Flush() { + util::WriteOrThrow(fd_, buf_.get(), builder_.position()); + builder_.Reset(); + } + + private: + void EnsureRemaining(std::size_t amount) { + if (static_cast<std::size_t>(builder_.size() - builder_.position()) < amount) { + Flush(); + } + } + + util::scoped_malloc buf_; + double_conversion::StringBuilder builder_; + double_conversion::DoubleToStringConverter convert_; + int fd_; +}; +} // namespace + +PrintARPA::PrintARPA(const VocabReconstitute &vocab, const std::vector<uint64_t> &counts, const HeaderInfo* header_info, int out_fd) + : vocab_(vocab), out_fd_(out_fd) { + std::stringstream stream; + + if (header_info) { + stream << "# Input file: " << header_info->input_file << '\n'; + stream << "# Token count: " << header_info->token_count << '\n'; + stream << "# Smoothing: Modified Kneser-Ney" << '\n'; + } + stream << "\\data\\\n"; + for (size_t i = 0; i < counts.size(); ++i) { + stream << "ngram " << (i+1) << '=' << counts[i] << '\n'; + } + stream << '\n'; + std::string as_string(stream.str()); + util::WriteOrThrow(out_fd, as_string.data(), as_string.size()); +} + +void PrintARPA::Run(const ChainPositions &positions) { + UTIL_TIMER("(%w s) Wrote ARPA file\n"); + OutputManager out(out_fd_); + for (unsigned order = 1; order <= positions.size(); ++order) { + out << "\\" << order << "-grams:" << '\n'; + for (NGramStream stream(positions[order - 1]); stream; ++stream) { + // Correcting for numerical precision issues. Take that IRST. + out << std::min(0.0f, stream->Value().complete.prob) << '\t' << vocab_.Lookup(*stream->begin()); + for (const WordIndex *i = stream->begin() + 1; i != stream->end(); ++i) { + out << ' ' << vocab_.Lookup(*i); + } + float backoff = stream->Value().complete.backoff; + if (backoff != 0.0) + out << '\t' << backoff; + out << '\n'; + } + out << '\n'; + } + out << "\\end\\\n"; +} + +}} // namespaces diff --git a/klm/lm/builder/print.hh b/klm/lm/builder/print.hh new file mode 100644 index 00000000..aa932e75 --- /dev/null +++ b/klm/lm/builder/print.hh @@ -0,0 +1,102 @@ +#ifndef LM_BUILDER_PRINT__ +#define LM_BUILDER_PRINT__ + +#include "lm/builder/ngram.hh" +#include "lm/builder/multi_stream.hh" +#include "lm/builder/header_info.hh" +#include "util/file.hh" +#include "util/mmap.hh" +#include "util/string_piece.hh" + +#include <ostream> + +#include <assert.h> + +// Warning: print routines read all unigrams before all bigrams before all +// trigrams etc. So if other parts of the chain move jointly, you'll have to +// buffer. + +namespace lm { namespace builder { + +class VocabReconstitute { + public: + // fd must be alive for life of this object; does not take ownership. + explicit VocabReconstitute(int fd); + + const char *Lookup(WordIndex index) const { + assert(index < map_.size() - 1); + return map_[index]; + } + + StringPiece LookupPiece(WordIndex index) const { + return StringPiece(map_[index], map_[index + 1] - 1 - map_[index]); + } + + std::size_t Size() const { + // There's an extra entry to support StringPiece lengths. + return map_.size() - 1; + } + + private: + util::scoped_memory memory_; + std::vector<const char*> map_; +}; + +// Not defined, only specialized. +template <class T> void PrintPayload(std::ostream &to, const Payload &payload); +template <> inline void PrintPayload<uint64_t>(std::ostream &to, const Payload &payload) { + to << payload.count; +} +template <> inline void PrintPayload<Uninterpolated>(std::ostream &to, const Payload &payload) { + to << log10(payload.uninterp.prob) << ' ' << log10(payload.uninterp.gamma); +} +template <> inline void PrintPayload<ProbBackoff>(std::ostream &to, const Payload &payload) { + to << payload.complete.prob << ' ' << payload.complete.backoff; +} + +// template parameter is the type stored. +template <class V> class Print { + public: + explicit Print(const VocabReconstitute &vocab, std::ostream &to) : vocab_(vocab), to_(to) {} + + void Run(const ChainPositions &chains) { + NGramStreams streams(chains); + for (NGramStream *s = streams.begin(); s != streams.end(); ++s) { + DumpStream(*s); + } + } + + void Run(const util::stream::ChainPosition &position) { + NGramStream stream(position); + DumpStream(stream); + } + + private: + void DumpStream(NGramStream &stream) { + for (; stream; ++stream) { + PrintPayload<V>(to_, stream->Value()); + for (const WordIndex *w = stream->begin(); w != stream->end(); ++w) { + to_ << ' ' << vocab_.Lookup(*w) << '=' << *w; + } + to_ << '\n'; + } + } + + const VocabReconstitute &vocab_; + std::ostream &to_; +}; + +class PrintARPA { + public: + // header_info may be NULL to disable the header + explicit PrintARPA(const VocabReconstitute &vocab, const std::vector<uint64_t> &counts, const HeaderInfo* header_info, int out_fd); + + void Run(const ChainPositions &positions); + + private: + const VocabReconstitute &vocab_; + int out_fd_; +}; + +}} // namespaces +#endif // LM_BUILDER_PRINT__ diff --git a/klm/lm/builder/sort.hh b/klm/lm/builder/sort.hh new file mode 100644 index 00000000..9989389b --- /dev/null +++ b/klm/lm/builder/sort.hh @@ -0,0 +1,103 @@ +#ifndef LM_BUILDER_SORT__ +#define LM_BUILDER_SORT__ + +#include "lm/builder/multi_stream.hh" +#include "lm/builder/ngram.hh" +#include "lm/word_index.hh" +#include "util/stream/sort.hh" + +#include "util/stream/timer.hh" + +#include <functional> +#include <string> + +namespace lm { +namespace builder { + +template <class Child> class Comparator : public std::binary_function<const void *, const void *, bool> { + public: + explicit Comparator(std::size_t order) : order_(order) {} + + inline bool operator()(const void *lhs, const void *rhs) const { + return static_cast<const Child*>(this)->Compare(static_cast<const WordIndex*>(lhs), static_cast<const WordIndex*>(rhs)); + } + + std::size_t Order() const { return order_; } + + protected: + std::size_t order_; +}; + +class SuffixOrder : public Comparator<SuffixOrder> { + public: + explicit SuffixOrder(std::size_t order) : Comparator<SuffixOrder>(order) {} + + inline bool Compare(const WordIndex *lhs, const WordIndex *rhs) const { + for (std::size_t i = order_ - 1; i != 0; --i) { + if (lhs[i] != rhs[i]) + return lhs[i] < rhs[i]; + } + return lhs[0] < rhs[0]; + } + + static const unsigned kMatchOffset = 1; +}; + +class ContextOrder : public Comparator<ContextOrder> { + public: + explicit ContextOrder(std::size_t order) : Comparator<ContextOrder>(order) {} + + inline bool Compare(const WordIndex *lhs, const WordIndex *rhs) const { + for (int i = order_ - 2; i >= 0; --i) { + if (lhs[i] != rhs[i]) + return lhs[i] < rhs[i]; + } + return lhs[order_ - 1] < rhs[order_ - 1]; + } +}; + +class PrefixOrder : public Comparator<PrefixOrder> { + public: + explicit PrefixOrder(std::size_t order) : Comparator<PrefixOrder>(order) {} + + inline bool Compare(const WordIndex *lhs, const WordIndex *rhs) const { + for (std::size_t i = 0; i < order_; ++i) { + if (lhs[i] != rhs[i]) + return lhs[i] < rhs[i]; + } + return false; + } + + static const unsigned kMatchOffset = 0; +}; + +// Sum counts for the same n-gram. +struct AddCombiner { + bool operator()(void *first_void, const void *second_void, const SuffixOrder &compare) const { + NGram first(first_void, compare.Order()); + // There isn't a const version of NGram. + NGram second(const_cast<void*>(second_void), compare.Order()); + if (memcmp(first.begin(), second.begin(), sizeof(WordIndex) * compare.Order())) return false; + first.Count() += second.Count(); + return true; + } +}; + +// The combiner is only used on a single chain, so I didn't bother to allow +// that template. +template <class Compare> class Sorts : public FixedArray<util::stream::Sort<Compare> > { + private: + typedef util::stream::Sort<Compare> S; + typedef FixedArray<S> P; + + public: + void push_back(util::stream::Chain &chain, const util::stream::SortConfig &config, const Compare &compare) { + new (P::end()) S(chain, config, compare); + P::Constructed(); + } +}; + +} // namespace builder +} // namespace lm + +#endif // LM_BUILDER_SORT__ |